Infusing and Augmenting Product Intelligence from Edge to Cloud
From edge inference to agentic intelligence – we build trusted, real-time AI systems for smarter, adaptive, and personalized product experiences
Why MosChip for AI Engineering?
Engineering Purpose-driven Intelligence
400+ Embedded and Digital Engineering projects delivered
75+ AI Models with customizable inference pipelines
125+ Data-driven and Analytics projects across industries
Hardware to Agentic AI accelerators for edge systems
Over 30% acceleration in intelligent IoT & cloud-native development
What We Deliver?
On-device inference, embedded vision/audio, sensor fusion, low-latency personalization
Scalable ML pipelines, predictive analytics, digital twins, simulation environments
Conversational UX, copilots, generative design, workflow automation
Perceive → Interpret → Decide → Engage frameworks, adaptive decision-making, explainable autonomy
AgenticSky™ - Adaptive autonomy cores for Agentic AI acceleration in products.
DigitalSky GenAIoT™ - 75+ Core AI models, 30+ Edge AI models, ~20 GenAI solutions.
Why Use DigitalSky & AgenticSky?
- No Licensing. No Royalty. No Lock-in.
- Built to accelerate your connected intelligent product journey
- Fully customizable to your product constraints and context
Key Technologies
Empowering Intelligent, Agentic, and Scalable AI Engineering Across Devices, Edge, and Cloud
Edge AI & On-Device Intelligence
Model Optimization:
Quantization, pruning, distillation for low-power AI workloads
Edge Deployment:
Deployment on Edge SoCs – on leading hardware platforms
Inference Runtime:
TensorFlow Lite, ONNX Runtime, TensorRT
Lightweight Models:
AI on MCUs & FPGAs - lightweight inferencing
Cloud & Scalable AI Infrastructure
Cloud AI Platforms:
Integration of AI/ML pipelines with leading public cloud infrastructures and systems
Data Pipelines:
Pre-processing, auto-labeling, feature extraction, pipeline orchestration
Model Training & Serving:
Custom MLOps pipelines, model versioning, GPU-based fine-tuning, containerization
Digital Twins & Simulation:
Lightweight control-loop simulations, primarily at edge-device or embedded stack level
GenAI Solutions
LLM Integration:
Open-source model tuning using LLaMA, Mistral, Gemma, and GPT variants for device or edge-side use
Multi-modal AI:
Vision-language models for smart vision, voice and gesture interfaces on embedded devices
Prompt Engineering & RAG:
Contextual GenAI flows using Retrieval-Augmented Generation (RAG) with domain datasets
Private & Hybrid GenAI:
Embedded or lightweight container-based execution for constrained or private edge environments
Agentic AI Systems
AgenticSky Cores:
Modular, event-driven, context-aware logic units for on-device autonomy
Explainability & Reasoning:
Lightweight observability layers, confidence scoring, and AI decision audit trails
Multi-agent Collaboration:
Coordination across edge devices (e.g., wearables, gateways, machines)
Realtime Edge Autonomy:
Perception-to-Action loops, OTA model updates, fallback logic on microcontrollers
DevOps & AI Lifecycle Toolchains
ModelOps:
Lightweight model monitoring, rollback support, on-device version control
Secure Deployment:
Model encryption, access provisioning, secure OTA inferencing support
AI Integration Frameworks:
PyTorch, TensorFlow Lite, Keras, Hugging Face, ONNX
Featured Case Study
Key Phrase Recognition for Low Power FPGA Devices
We work with a wide technology stack including TensorFlow Lite, PyTorch, Keras, Caffe2, OpenCV, Hugging Face, LLaMA, EdgeOps, MLOps, and OpenVX, ensuring flexibility, scalability, and interoperability.
Yes. We help port or optimize your existing models for edge inference, retraining, quantization, or integration into our stack.
Generative AI creates context based content or responses, while Agentic AI adds autonomy, allowing systems to interpret, decide, and act purposefully within the defined goals, ensuring continuous adaptation and learning.
You can start by connecting with our experts to discuss your AI goals. Together, we’ll identify opportunities, define the architecture, and engineer intelligent solutions tailored to your vision.
Absolutely! Our modular AI accelerators (DigitalSky and AgenticSky) are designed for seamless integration with existing hardware and software ecosystems, accelerating intelligent transformation without rebuilding from scratch.
AgenticSky is MosChip’s suite of Agentic AI accelerators designed to bring autonomy, context-awareness, and real-time adaptability to edge and embedded systems. It includes reusable cores, AI pipelines, and frameworks that enable rapid prototyping and deployment of agentic behavior in devices – reducing time-to-market without licensing or royalty overheads.
Infusing and Augmenting Product Intelligence from Edge to Cloud
From edge inference to agentic intelligence – we build trusted, real-time AI systems for smarter, adaptive, and personalized product experiences
Why MosChip for AI Engineering?
Engineering Purpose-driven Intelligence
400+ Embedded and Digital Engineering projects delivered
75+ AI Models with customizable inference pipelines
125+ Data-driven and Analytics projects across industries
Hardware to Agentic AI accelerators for edge systems
Over 30% acceleration in intelligent IoT & cloud-native development
On-device inference, embedded vision/audio, sensor fusion, low-latency personalization
Scalable ML pipelines, predictive analytics, digital twins, simulation environments
Conversational UX, copilots, generative design, workflow automation
Perceive → Interpret → Decide → Engage frameworks, adaptive decision-making, explainable autonomy
AgenticSky™ - Adaptive autonomy cores for Agentic AI acceleration in products.
DigitalSky GenAIoT™ - 75+ Core AI models, 30+ Edge AI models, ~20 GenAI solutions.
Why Use DigitalSky & AgenticSky?
- No Licensing. No Royalty. No Lock-in.
- Built to accelerate your connected intelligent product journey
- Fully customizable to your product constraints and context
What We Deliver?
Key Technologies
Empowering Intelligent, Agentic, and Scalable AI Engineering Across Devices, Edge, and Cloud
Edge AI & On-Device Intelligence
Model Optimization:
Quantization, pruning, distillation for low-power AI workloads
Inference Runtime:
TensorFlow Lite, ONNX Runtime, TensorRT
Edge Deployment:
Deployment on Edge SoCs – on leading hardware platforms
Lightweight Models:
AI on MCUs & FPGAs - lightweight inferencing
Cloud & Scalable AI Infrastructure
Cloud AI Platforms:
Integration of AI/ML pipelines with leading public cloud infrastructures and systems
Model Training & Serving:
Custom MLOps pipelines, model versioning, GPU-based fine-tuning, containerization
Data Pipelines:
Pre-processing, auto-labeling, feature extraction, pipeline orchestration
Digital Twins & Simulation:
Lightweight control-loop simulations, primarily at edge-device or embedded stack level
GenAI Solutions
LLM Integration:
Open-source model tuning using LLaMA, Mistral, Gemma, and GPT variants for device or edge-side use
Prompt Engineering & RAG:
Contextual GenAI flows using Retrieval-Augmented Generation (RAG) with domain datasets
Multi-modal AI:
Vision-language models for smart vision, voice and gesture interfaces on embedded devices
Private & Hybrid GenAI:
Embedded or lightweight container-based execution for constrained or private edge environments
Agentic AI Systems
AgenticSky Cores:
Modular, event-driven, context-aware logic units for on-device autonomy
Multi-agent Collaboration:
Coordination across edge devices (e.g., wearables, gateways, machines)
Explainability & Reasoning:
Lightweight observability layers, confidence scoring, and AI decision audit trails
Realtime Edge Autonomy:
Perception-to-Action loops, OTA model updates, fallback logic on microcontrollers
DevOps & AI Lifecycle Toolchains
ModelOps:
Lightweight model monitoring, rollback support, on-device version control
AI Integration Frameworks:
PyTorch, TensorFlow Lite, Keras, Hugging Face, ONNX
Secure Deployment:
Model encryption, access provisioning, secure OTA inferencing support
Featured Case Study
Key Phrase Recognition for Low Power FPGA Devices
We work with a wide technology stack including TensorFlow Lite, PyTorch, Keras, Caffe2, OpenCV, Hugging Face, LLaMA, EdgeOps, MLOps, and OpenVX, ensuring flexibility, scalability, and interoperability.
We help port or optimize your existing models for edge inference, retraining, quantization, or integration into our stack.
Generative AI creates context based content or responses, while Agentic AI adds autonomy, allowing systems to interpret, decide, and act purposefully within the defined goals, ensuring continuous adaptation and learning.
You can start by connecting with our experts to discuss your AI goals. Together, we’ll identify opportunities, define the architecture, and engineer intelligent solutions tailored to your vision.
Absolutely! Our modular AI accelerators (DigitalSky and AgenticSky) are designed for seamless integration with existing hardware and software ecosystems, accelerating intelligent transformation without rebuilding from scratch.
AgenticSky is MosChip’s suite of Agentic AI accelerators designed to bring autonomy, context-awareness, and real-time adaptability to edge and embedded systems. It includes reusable cores, AI pipelines, and frameworks that enable rapid prototyping and deployment of agentic behavior in devices – reducing time-to-market without licensing or royalty overheads.
